Context representation and fusion via likelihood masks for target tracking

Authors:
Lauro Snidaro;Ingrid Visentini;Gian Luca Foresti
Affiliations:
Department of Mathematics and Computer Science, University of Udine, Italy;Department of Mathematics and Computer Science, University of Udine, Italy;Department of Mathematics and Computer Science, University of Udine, Italy
Venue:
HAIS'11 Proceedings of the 6th international conference on Hybrid artificial intelligent systems - Volume Part II
Year:
2011

Citing 5
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Abstract

The inclusion of contextual information in low-level fusion processes is a promising research direction still scarcely explored. In this paper we propose a framework for integrating contextual knowledge in a fusion process in order to improve the estimation of a target's state. In particular, we will describe how contextual information can take the form of likelihood maps to be fused with the sensor's likelihood function in order to encode the dependence of the observation from the context.